[R] F-test where the coefficients in the H_0 is nonzero

Annaert Jan j@n@@nn@ert @end|ng |rom u@ntwerpen@be
Fri Aug 3 07:54:36 CEST 2018

You can easily test linear restrictions using the function linearHypothesis() from the car package.
There are several ways to set up the null hypothesis, but a straightforward one here is:
> library(car)
> x <- rnorm(10)
> y <- x+rnorm(10)
> linearHypothesis(lm(y~x), c("(Intercept)=0", "x=1"))
Linear hypothesis test

(Intercept) = 0
x = 1

Model 1: restricted model
Model 2: y ~ x

  Res.Df     RSS Df Sum of Sq      F Pr(>F)
1     10 10.6218                           
2      8  9.0001  2    1.6217 0.7207 0.5155


From: R-help <r-help-bounces using r-project.org> on behalf of John <miaojpm using gmail.com>
Date: Thursday, 2 August 2018 at 10:44
To: r-help <r-help using r-project.org>
Subject: [R] F-test where the coefficients in the H_0 is nonzero


   I try to run the regression
   y = beta_0 + beta_1 x
   and test H_0: (beta_0, beta_1) =(0,1) against H_1: H_0 is false
   I believe I can run the regression
   (y-x) = beta_0 +beta_1‘ x
   and do the regular F-test (using lm functio) where the hypothesized
coefficients are all zero.

   Is there any function in R that deal with the case where the
coefficients are nonzero?


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